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EFFICIENT AND ACCURATE CALCULATION OF DISCRETE FREQUENCY RESPONSE FUNCTIONS AND IMPULSE RESPONSE FUNCTIONS

机译:离散频率响应函数和脉冲响应函数的有效而精确的计算

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Modal properties of a structure can be identified by experimental modal analysis (EMA). Discrete frequency response functions (FRFs) and impulse response functions (IRFs) between responses and excitation are bases for EMA. In calculation of a discrete FRF, discrete Fourier transform (DFT) is applied to both response and excitation data series, and a transformed data series in DFT is virtually extended to have an infinite length and be periodic with a period equal to the length of the series; the resulting periodicity can be physically incorrect in some cases, which depends on an excitation technique used. There are various excitation techniques in EMA, and periodic extension in DFT for EMA using periodic random and burst random excitation is physically correct. However, EMA using periodic random excitation needs a relatively long excitation time to have responses to be steady-state and periodic, and EMA using burst random excitation needs a long sampling period for responses to decay to zero, which can result in relatively long response and excitation data series and necessitate a large number of spectral lines for associated DFTs, especially for a high sampling frequency. An efficient and accurate methodology for calculating discrete FRFs and IRFs is proposed here, by which fewer spectral lines are needed and accuracies of resulting FRFs and IRFs can be maintained. The relationship between an IRFfrom the proposed methodology and that from the least-squares method is shown. A new coherence function that can evaluate qualities of FRFs and IRFs from the proposed methodology in the frequency domain is used, from which meaningful coherence function values can be obtained even with response and excitation series of one sampling period. Based on the new coherence function, a fitting index is used to evaluate overall qualities of the FRFs and IRFs. The proposed methodology was numerically and experimentally applied to a two-degree-of-freedom mass-spring-damper system and an aluminum plate to estimate their FRFs, respectively. In the numerical example, FRFs from the proposed methodology agree well with the theoretical one; in the experimental example, a FRF from the proposed methodology with a random impact series agreed well with the benchmark one from a single impact test.
机译:可以通过实验模态分析(EMA)来识别结构的模态特性。响应和激励之间的离散频率响应函数(FRF)和脉冲响应函数(IRF)是EMA的基础。在离散FRF的计算中,将离散傅里叶变换(DFT)应用于响应和激励数据序列,并且DFT中的变换数据序列实际上被扩展为具有无限长度,并且具有等于周期长度的周期性。系列;在某些情况下,所产生的周期性在物理上可能是不正确的,这取决于所使用的激励技术。 EMA中有多种激励技术,而使用周期性随机和突发随机激励的EMA的DFT中的周期性扩展在物理上是正确的。但是,使用周期性随机激励的EMA需要相对较长的激励时间才能使响应达到稳态和周期性,而使用突发随机激励的EMA需要较长的采样周期才能使响应衰减为零,这可能导致较长的响应和激发数据序列,并为关联的DFT(特别是对于高采样频率)需要大量的光谱线。本文提出了一种高效,准确的计算离散FRF和IRF的方法,通过该方法,所需的光谱线更少,并且可以保持所得FRF和IRF的准确性。显示了所提出的方法与最小二乘法所产生的IRF之间的关系。使用了一种新的相干函数,该函数可以从所提出的方法在频域中评估FRF和IRF的质量,即使在一个采样周期的响应和激励序列下,也可以从中获得有意义的相干函数值。基于新的相干函数,拟合指数用于评估FRF和IRF的整体质量。所提出的方法在数值和实验上分别应用于两自由度质量弹簧-阻尼器系统和铝板,以估计其FRF。在数值示例中,所提出方法的FRF与理论方法非常吻合。在实验示例中,所提出方法的FRF和随机影响序列与单次冲击测试的基准测试结果非常吻合。

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